{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Population Data from CSV\n",
    "\n",
    "This notebooks reads sample population data from `data/atlantis.csv` and plots it using Matplotlib. Edit `data/atlantis.csv` and re-run this cell to see how the plots change!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import pandas\n",
    "\n",
    "df = pandas.read_csv('../data/atlantis.csv')\n",
    "x = df['year']\n",
    "y = df['population']\n",
    "\n",
    "plt.plot(x,y)\n",
    "plt.title(\"Population of Atlantis\")\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Population')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.4 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  },
  "orig_nbformat": 4,
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